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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitemtc-m16b.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier6qtX3pFwXQZGivnK2Y/Qbs7T
Repositorysid.inpe.br/mtc-m17@80/2007/05.18.14.24   (restricted access)
Last Update2007:05.18.14.26.07 (UTC) marciana
Metadata Repositorysid.inpe.br/mtc-m17@80/2007/05.18.14.24.43
Metadata Last Update2020:10.01.15.58.08 (UTC) administrator
Secondary KeyINPE--PRE/
DOI10.1109/IGARSS.2007.4423869
Citation KeyStechAlcBarNovShi:2007:TuAmFl
TitleTurbidity in the Amazon Floodplain Assessed Through a Spatial Regression Model Applied to Fraction Images Derived From MODIS/Terra
FormatCD-ROM; DVD; On-line; Papel.
Year2007
Access Date2024, May 18
Secondary TypePRE CI
Number of Files1
Size289 KiB
2. Context
Author1 Stech, José Luiz
2 Alcântara, Enner
3 Barbosa, Cláudio Clemente de Faria
4 Novo, Evlyn Márcia Leão de Moraes
5 Shimabukuro, Yosio Edemir
Resume Identifier1
2
3
4
5 8JMKD3MGP5W/3C9JJCQ
Group1 DSR-INPE-MCT-BR
2 DSR-INPE-MCT-BR
3 DPI-INPE-MCT-BR
4 DSR-INPE-MCT-BR
5 DSR-INPE-MCT-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
4 Instituto Nacional de Pesquisas Espaciais (INPE)
5 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 stech@dsr.inpe.br
2 enner@dsr.inpe.br
3 claudio@dpi.inpe.br
4 evlyn@dsr.inpe.br
5 yosio@dsr.inpe.br
e-Mail Addressenner@dsr.inpe.br
Conference NameInternational Geoscience and Remote Sensing Symposium, (IGARSS).
Conference LocationBarcelona, Spain.
PublisherIEEE
Pages4550 - 4553
Book TitleProceedings
Tertiary TypeArtigos
History (UTC)2007-12-21 17:51:14 :: ennerha -> marciana ::
2008-04-04 17:30:23 :: marciana -> administrator ::
2014-09-02 16:40:17 :: administrator -> marciana :: 2007
2014-09-05 18:43:23 :: marciana -> administrator :: 2007
2020-10-01 15:58:08 :: administrator -> simone :: 2007
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Keywordsturbidity
spatial regression model
MODIS
fraction image
Amazon floodplain
AbstractThe objective of this paper was to estimate turbidity in the Curuai floodplain during high water level. Spatial regression models were developed using fraction images derived from a Linear Spectral Mixture Model (LSMM) applied to a MODIS/Terra image and turbidity in-situ data. As the turbidity in-situ data showed spatial autocorrelation, they had been divided into four spatial regimes (clusters). Thus, a spatial regression model was developed for each spatial regime. Through the Akaike information criterion (AIC) it was verified which spatial regime showed the best fit in the spatial regression model. The results showed that the best fit was presented by the spatial regime 4 (r2=0.80, p<0.05). The spatial regression model developed for the spatial regime 4 was then applied to all floodplain lakes. Spatial regression models show potential for turbidity studies in aquatic systems for considering spatial dependence between samples.
AreaSRE
Arrangement 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > Turbidity in the...
Arrangement 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Turbidity in the...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
Languageen
Target FileIgarss.pdf
User Groupadministrator
ennerha
marciana
Reader Groupadministrator
marciana
Visibilityshown
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
LinkingTrabalho Vinculado à Tese/Dissertação
Next Higher Units8JMKD3MGPCW/3EQCCU5
8JMKD3MGPCW/3ER446E
Host Collectionlcp.inpe.br/ignes/2004/02.12.18.39
cptec.inpe.br/walmeida/2003/04.25.17.12
6. Notes
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